A1 Vertaisarvioitu alkuperäisartikkeli tieteellisessä lehdessä

Development of prediction model for alanine transaminase elevations during the first 6 months of conventional synthetic DMARD treatment




TekijätKuusalo Laura, Venäläinen Mikko, Kirjala Heidi, Saranpää Sofia, Elo Laura L, Pirila Laura

KustantajaNATURE PORTFOLIO

Julkaisuvuosi2023

JournalScientific Reports

Tietokannassa oleva lehden nimiSCIENTIFIC REPORTS

Lehden akronyymiSCI REP-UK

Artikkelin numero12943

Vuosikerta13

Sivujen määrä9

ISSN2045-2322

DOIhttps://doi.org/10.1038/s41598-023-39694-2

Verkko-osoitehttps://doi.org/10.1038/s41598-023-39694-2

Rinnakkaistallenteen osoitehttps://research.utu.fi/converis/portal/detail/Publication/180857000


Tiivistelmä
Frequent laboratory monitoring is recommended for early identification of toxicity when initiating conventional synthetic disease-modifying antirheumatic drugs (csDMARDs). We aimed at developing a risk prediction model to individualize laboratory testing at csDMARD initiation. We identified inflammatory joint disease patients (N = 1196) initiating a csDMARD in Turku University Hospital 2013-2019. Baseline and follow-up safety monitoring results were drawn from electronic health records. For rheumatoid arthritis patients, diagnoses and csDMARD initiation/cessation dates were manually confirmed. Primary endpoint was alanine transaminase (ALT) elevation of more than twice the upper limit of normal (ULN) within 6 months after treatment initiation. Computational models for predicting incident ALT elevations were developed using Lasso Cox proportional hazards regression with stable iterative variable selection (SIVS) and were internally validated against a randomly selected test cohort (1/3 of the data) that was not used for training the models. Primary endpoint was reached in 82 patients (6.9%). Among baseline variables, Lasso model with SIVS predicted subsequent ALT elevations of > 2 x ULN using higher ALT, csDMARD other than methotrexate or sulfasalazine and psoriatic arthritis diagnosis as important predictors, with a concordance index of 0.71 in the test cohort. Respectively, at first follow-up, in addition to baseline ALT and psoriatic arthritis diagnosis, also ALT change from baseline was identified as an important predictor resulting in a test concordance index of 0.72. Our computational model predicts ALT elevations after the first follow-up test with good accuracy and can help in optimizing individual testing frequency.

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Last updated on 2024-26-11 at 23:41